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bigcode/starcoder2-15b - GGUF
This repo contains GGUF format model files for bigcode/starcoder2-15b.
The files were quantized using machines provided by TensorBlock, and they are compatible with llama.cpp as of commit b4011.
Prompt template
Model file specification
Filename | Quant type | File Size | Description |
---|---|---|---|
starcoder2-15b-Q2_K.gguf | Q2_K | 5.768 GB | smallest, significant quality loss - not recommended for most purposes |
starcoder2-15b-Q3_K_S.gguf | Q3_K_S | 6.507 GB | very small, high quality loss |
starcoder2-15b-Q3_K_M.gguf | Q3_K_M | 7.492 GB | very small, high quality loss |
starcoder2-15b-Q3_K_L.gguf | Q3_K_L | 8.350 GB | small, substantial quality loss |
starcoder2-15b-Q4_0.gguf | Q4_0 | 8.443 GB | legacy; small, very high quality loss - prefer using Q3_K_M |
starcoder2-15b-Q4_K_S.gguf | Q4_K_S | 8.532 GB | small, greater quality loss |
starcoder2-15b-Q4_K_M.gguf | Q4_K_M | 9.183 GB | medium, balanced quality - recommended |
starcoder2-15b-Q5_0.gguf | Q5_0 | 10.265 GB | legacy; medium, balanced quality - prefer using Q4_K_M |
starcoder2-15b-Q5_K_S.gguf | Q5_K_S | 10.265 GB | large, low quality loss - recommended |
starcoder2-15b-Q5_K_M.gguf | Q5_K_M | 10.646 GB | large, very low quality loss - recommended |
starcoder2-15b-Q6_K.gguf | Q6_K | 12.201 GB | very large, extremely low quality loss |
starcoder2-15b-Q8_0.gguf | Q8_0 | 15.800 GB | very large, extremely low quality loss - not recommended |
Downloading instruction
Command line
Firstly, install Huggingface Client
pip install -U "huggingface_hub[cli]"
Then, downoad the individual model file the a local directory
huggingface-cli download tensorblock/starcoder2-15b-GGUF --include "starcoder2-15b-Q2_K.gguf" --local-dir MY_LOCAL_DIR
If you wanna download multiple model files with a pattern (e.g., *Q4_K*gguf
), you can try:
huggingface-cli download tensorblock/starcoder2-15b-GGUF --local-dir MY_LOCAL_DIR --local-dir-use-symlinks False --include='*Q4_K*gguf'
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Model tree for tensorblock/starcoder2-15b-GGUF
Base model
bigcode/starcoder2-15bDataset used to train tensorblock/starcoder2-15b-GGUF
Evaluation results
- pass@1 on CruxEval-Iself-reported48.100
- pass@1 on DS-1000self-reported33.800
- accuracy on GSM8K (PAL)self-reported65.100
- pass@1 on HumanEval+self-reported37.800
- pass@1 on HumanEvalself-reported46.300
- edit-smiliarity on RepoBench-v1.1self-reported74.080